HaLeR

In the HaLeR project, solutions for a flexible and adaptive MMI are to be developed. The developed methods should allow a system to react and adapt flexibly to human behavior when situations change. To this end, the University of Bremen will develop an approach that automatically recognizes the connections between individual behavioral segments and adapts them to new, similar situations so that upcoming behavioral segments can be predicted in a situationally appropriate manner. Thus, deviations in human behavior are detected. DFKI Bremen develops scenarios to test whether deviations in human behavior are detected when situations change and whether the behavior of the system within a man-machine collaboration is adapted accordingly. In this way, the flexibility of the MMI can be evaluated, e.g. it is evaluated whether and how the system successfully supports the human being despite changed movement (e.g. changed sequence of behavioral segments).

In order to detect deviations in the human's actions, both the human's movements by means of motion tracking and intrinsic motivations and evaluations of current situations are analyzed using EEG data. The data will be analyzed using learning methods developed by the Robotics Group of the University of Bremen, which has great expertise in the development of adaptive and robust learning architectures and learning methods. The focus is on methods that do not require large computing capacities. Thus, the methods can be applied in scenarios with limited resources, such as space missions. The focus of DFKI's work is on the development of test environments and the evaluation of methods developed by the robotics group at the University of Bremen.